Zhu X - Search Results

1

GraphNABP: Identifying nucleic acid-binding proteins with protein graphs and protein language models.

Li X, Wei Z, Hu Y, Zhu X. Li X, et al. Among authors: zhu x. Int J Biol Macromol. 2024 Sep 12;280(Pt 1):135599. doi: 10.1016/j.ijbiomac.2024.135599. Online ahead of print. Int J Biol Macromol. 2024. PMID: 39276905

2

NeuroPpred-SVM: A New Model for Predicting Neuropeptides Based on Embeddings of BERT.

Liu Y, Wang S, Li X, Liu Y, Zhu X. Liu Y, et al. Among authors: zhu x. J Proteome Res. 2023 Mar 3;22(3):718-728. doi: 10.1021/acs.jproteome.2c00363. Epub 2023 Feb 7. J Proteome Res. 2023. PMID: 36749151

3

Protein-DNA interface hotspots prediction based on fusion features of embeddings of protein language model and handcrafted features.

Li X, Wang GA, Wei Z, Wang H, Zhu X. Li X, et al. Among authors: zhu x. Comput Biol Chem. 2023 Dec;107:107970. doi: 10.1016/j.compbiolchem.2023.107970. Epub 2023 Oct 10. Comput Biol Chem. 2023. PMID: 37866116

4

MSTL-Kace: Prediction of Prokaryotic Lysine Acetylation Sites Based on Multistage Transfer Learning Strategy.

Wang GA, Yan X, Li X, Liu Y, Xia J, Zhu X. Wang GA, et al. Among authors: zhu x. ACS Omega. 2023 Oct 25;8(44):41930-41942. doi: 10.1021/acsomega.3c07086. eCollection 2023 Nov 7. ACS Omega. 2023. PMID: 37969991 Free PMC article.

5

NeuroPpred-SHE: An interpretable neuropeptides prediction model based on selected features from hand-crafted features and embeddings of T5 model.

Wen J, Ding Z, Wei Z, Xia H, Zhang Y, Zhu X. Wen J, et al. Among authors: zhu x. Comput Biol Med. 2024 Oct;181:109048. doi: 10.1016/j.compbiomed.2024.109048. Epub 2024 Aug 24. Comput Biol Med. 2024. PMID: 39182368

6

SGTCDA: Prediction of circRNA-drug sensitivity associations with interpretable graph transformers and effective assessment.

Xia H, Dong C, Chen X, Wei Z, Gu L, Zhu X. Xia H, et al. Among authors: zhu x. BMC Genomics. 2024 Nov 20;25(1):1113. doi: 10.1186/s12864-024-11022-6. BMC Genomics. 2024. PMID: 39567908 Free PMC article.

7

iPNHOT: a knowledge-based approach for identifying protein-nucleic acid interaction hot spots.

Zhu X, Liu L, He J, Fang T, Xiong Y, Mitchell JC. Zhu X, et al. BMC Bioinformatics. 2020 Jul 6;21(1):289. doi: 10.1186/s12859-020-03636-w. BMC Bioinformatics. 2020. PMID: 32631222 Free PMC article.

8

Protein-protein interface hot spots prediction based on a hybrid feature selection strategy.

Qiao Y, Xiong Y, Gao H, Zhu X, Chen P. Qiao Y, et al. Among authors: zhu x. BMC Bioinformatics. 2018 Jan 15;19(1):14. doi: 10.1186/s12859-018-2009-5. BMC Bioinformatics. 2018. PMID: 29334889 Free PMC article.

9

m5CPred-SVM: a novel method for predicting m5C sites of RNA.

Chen X, Xiong Y, Liu Y, Chen Y, Bi S, Zhu X. Chen X, et al. Among authors: zhu x. BMC Bioinformatics. 2020 Oct 30;21(1):489. doi: 10.1186/s12859-020-03828-4. BMC Bioinformatics. 2020. PMID: 33126851 Free PMC article.

10

BERT-Kcr: prediction of lysine crotonylation sites by a transfer learning method with pre-trained BERT models.

Qiao Y, Zhu X, Gong H. Qiao Y, et al. Among authors: zhu x. Bioinformatics. 2022 Jan 12;38(3):648-654. doi: 10.1093/bioinformatics/btab712. Bioinformatics. 2022. PMID: 34643684

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